NVIDIA CORP Q3 2026 earnings call

Thank you. Good afternoon, everyone, and welcome to NVIDIA's Conference Call for the Third Quarter of Fiscal 2026. With me today from NVIDIA are Jensen Huang, President and Chief Executive Officer, and Colette Kress, Executive Vice President and Chief Financial Officer. I'd like to remind you that our call is being Webcast Live on NVIDIA's Investor Relations website. The webcast will be available for replay until the conference call to discuss our financial results for the 4th quarter of fiscal 2026. The content of today's call is NVIDIA's property. It can't be reproduced or transcribed without our prior written consent. During this call, we may make forward-looking statements based on current expectations. These are subject to a number of significant risks and uncertainties, and our actual results may differ materially.

For a discussion of factors that could affect our future financial results and business, please refer to the disclosure in today's earnings release, our most recent forms 10-K and 10-Q, and the reports that we may file on Form 8-K with the Securities and Exchange Commission. All our statements are made as of today, November 19, 2025, based on information currently available to us. Except as required by law, we assume no obligation to update any such statements. During this call, we will discuss non-GAAP financial measures. You can find a reconciliation of these non-GAAP financial measures to GAAP financial measures in our CFO commentary, which is posted on our website. With that, let me turn the call over to Colette.

Thank you, Toshiya. We delivered another outstanding quarter with revenue of $57 billion, up 62% year-over-year, and a record sequential revenue growth of $10 billion, or 22%. Our customers continue to lean into three platform shifts, fueling exponential growth for Accelerated Computing, powerful AI models, and Agentic applications. Yet, we are still in the early innings of these transitions that will impact our work across every industry. We currently have visibility to $500 billion in Blackwell and Rubin revenue from the start of this year through the end of Calendar Year 2026. By executing our annual product cadence and extending our Performance leadership through Full-stack Design, we believe NVIDIA will be the superior choice for the $3 trillion-$4 trillion in annual AI infrastructure build we estimate by the end of the decade. Demand for AI infrastructure continues to exceed our expectations.

The clouds are sold out, and our GPU-installed base, both new and previous generations, including Blackwell, Hopper, and Ampere, is fully utilized. Record Q3 Data Center revenue of $51 billion increased 66% year-over-year, a significant feat at our scale. Compute grew 56% year-over-year, driven primarily by the GB300 ramp, while networking more than doubled given the onset of NVLink scale-up and robust Double-digit growth across Spectrum-X Ethernet and Quantum-X InfiniBand. The World Hyperscalers, a trillion-dollar industry, are transforming search, recommendations, and content understanding from Classical Machine Learning to Generative AI. NVIDIA CUDA excels at both and is the ideal platform for this transition, driving infrastructure investment measured in hundreds of billions of dollars. At Meta, AI recommendation systems are delivering higher quality and more relevant content, leading to more time spent on apps such as Facebook and Threads.

Analyst expectations for the top CSPs and Hyperscalers in 2026 aggregate CapEx have continued to increase and now sit roughly at $600 billion, more than $200 billion higher relative to the start of the year. We see the transition to Accelerated Computing and Generative AI across current Hyperscale workloads contributing toward roughly half of our long-term opportunity. Another growth pillar is the ongoing increase in compute spend driven by foundation model builders such as Anthropic, Mistral, OpenAI, Reflection, Safe Superintelligence, Thinking Machines Lab, and xAI, all scaling compute aggressively to scale intelligence. The three scaling laws, Pre-training, Post-training, and Inference remain intact. In fact, we see a positive virtuous cycle emerging whereby the three scaling laws and access to compute are generating better intelligence and, in turn, increasing adoption and profits.

OpenAI recently shared that their weekly user base has grown to $800 million, Enterprise customers have increased to 1 million, and that their gross margins were healthy. While Anthropic recently reported that its annualized run rate revenue has reached $7 billion as of last month, up from $1 billion at the start of the year. We are also witnessing a proliferation of Agentic AI across various industries and tasks. Companies such as Cursor, Anthropic, OpenEvidence, Epic, and Abridge are experiencing a surge in user growth as they supercharge the existing workforce, delivering unquestionable ROI for coders and healthcare professionals. The world's most important enterprise software platforms like ServiceNow, CrowdStrike, and SAP are integrating NVIDIA's Accelerated Computing and AI stack. Our new partner, Palantir, is supercharging the incredibly popular ontology platform with NVIDIA CUDA-X libraries and AI models for the 1st time.

Previously, like most enterprise software platforms, Ontology runs only on CPUs. Lowe's is leveraging the platform to build supply chain agility, reducing costs and improving customer satisfaction. Enterprises broadly are leveraging AI to boost productivity, increase efficiency, and reduce costs. RBC is leveraging Agentic AI to drive significant Analyst Productivity, slashing report generation time from hours to minutes. AI and digital twins are helping Unilever accelerate content creation by 2x and cut costs by 50%. Salesforce's Engineering team has seen at least a 30% productivity increase in new code development after adopting Cursor. This past quarter, we announced AI factory and infrastructure projects amounting to an aggregate of 5 million GPUs. This demand spans every market: CSPs, Sovereigns, Model Builders, Enterprises, and Supercomputing Centers, and includes multiple landmark buildouts.

xAI's Colossus 2, the world's 1st Gigawatt-scale Data Center, Lilly's AI factory for drug discovery, the pharmaceutical industry's most powerful Data Center. Just today, AWS and HUMAIN expanded their partnership, including the deployment of up to 150,000 AI accelerators, including our GB300. xAI and HUMAIN also announced a partnership in which the two will jointly develop a network of world-class Data Centers anchored by the flagship 500-megawatt facility. Blackwell gained further momentum in Q3 as GB300 crossed over GB200 and contributed roughly 2/3 of the total Blackwell revenue. The transition to GB300 has been seamless, with production shipments to the major Cloud Service providers, Hyperscalers, and GPU clouds, and is already driving their growth. The Hopper platform, in its 13th quarter since inception, recorded approximately $2 billion in revenue in Q3. H20 sales were approximately $50 million.

Sizable purchase orders never materialized in the quarter due to geopolitical issues and the increasingly competitive market in China. While we were disappointed in the current state that prevents us from shipping more competitive Data Center compute products to China, we are committed to continued engagement with the U.S. and China governments and will continue to advocate for America's ability to compete around the world. To establish a sustainable leadership position in AI computing, America must win the support of every developer and be the platform of choice for every commercial business, including those in China. The Rubin platform is on track to ramp in the 2nd half of 2026. Powered by seven chips, the Vera Rubin platform will once again deliver an X-factor improvement in Performance relative to Blackwell.

We have received silicon back from our supply chain partners and are happy to report that NVIDIA teams across the world are executing the bring-up beautifully. Rubin is our 3rd generation Rack-scale System, substantially redefined the manufacturability while remaining compatible with Grace Blackwell. Our Supply Chain Data Center Ecosystem and Cloud Partners have now mastered the Build-to-installation process of NVIDIA's Rack Architecture. Our ecosystem will be ready for a fast Rubin ramp. Our annual X-factor Performance leap increases Performance per dollar while driving down computing costs for our customers. The long useful life of NVIDIA's CUDA GPUs is a significant TCO advantage over accelerators. CUDA's compatibility and our massive installed base extend the life of NVIDIA systems well beyond their original estimated useful life. For more than two decades, we have optimized the CUDA ecosystem, improving existing workloads, accelerating new ones, and increasing throughput with every software release.

Most accelerators without CUDA and NVIDIA's time-tested and versatile architecture became obsolete within a few years as model technologies evolve. Thanks to CUDA, the A100 GPUs we shipped six years ago are still running at full utilization today, powered by vastly improved software stack. We have evolved over the past 25 years from a Gaming GPU company to now an AI Data Center Infrastructure company. Our ability to innovate across the CPU, the GPU, networking, and software, and ultimately drive down cost per token, is unmatched across the industry. Our networking business, purpose-built for AI and now the largest in the world, generated revenue of $8.2 billion, up 162% year-over-year, with NVLink, InfiniBand, and Spectrum-X Ethernet all contributing to growth. We are winning in Data Center Networking as the majority of AI deployments now include our switches with Ethernet GPU attach rates roughly on par with InfiniBand.

Meta, Microsoft, Oracle, and xAI are building GW AI factories with Spectrum-X Ethernet switches, and each will run its Operating System of choice, highlighting the flexibility and openness of our platform. We recently introduced Spectrum-XGS, a scale-across technology that enables gigascale AI factories. NVIDIA is the only company with AI Scale-up, Scale-out, and Scale-across platforms, reinforcing our unique position in the market as the AI infrastructure provider. Customer interest in NVLink Fusion continues to grow. We announced a strategic collaboration with Fujitsu in October, where we will integrate Fujitsu's CPUs and NVIDIA GPUs via NVLink Fusion, connecting our large ecosystems. We also announced a collaboration with Intel to develop multiple generations of custom Data Center and PC products, connecting NVIDIA and Intel's ecosystems using NVLink.

This week at Supercomputing 2025, Arm announced that it will be integrating NVLink IP for customers to build CPU SoCs that connect with NVIDIA. Currently on its 5th generation, NVLink is the only proven scale-up technology available on the market today. In the latest MLPerf Training Results, Blackwell Ultra delivered 5x faster time to train than Hopper. NVIDIA swept every benchmark. Notably, NVIDIA is the only training platform to leverage bridge FP4 while meeting MLPerf's strict accuracy standards. In semi-analysis Inference max benchmark, Blackwell achieved the highest Performance and lowest total cost of ownership across every model and use case. Particularly important is Blackwell's NVLink's Performance on a mixture of experts, the architecture for the world's most popular reasoning models. On DeepSeek-R1, Blackwell delivered 10x higher Performance per watt and 10x lower cost per token versus H200, a huge generational leap fueled by our extreme code design approach.

NVIDIA Dynamo, an open-source, low-latency modular Inference framework, has now been adopted by every major cloud service provider. Leveraging Dynamo's enablement and disaggregated Inference, the resulting increase in Performance of Complex AI models such as MoE models, AWS, Google Cloud, Microsoft Azure, and OCI have boosted AI Inference Performance for Enterprise Cloud customers. We are working on a strategic partnership with OpenAI focused on helping them build and deploy at least 10 GW of Data Centers. in addition, we have the opportunity to invest in the company. We serve OpenAI through their cloud partners, Microsoft Azure, OCI, and CoreWeave. We will continue to do so for the foreseeable future. As they continue to scale, we are delighted to support the company to add self-build infrastructure, and we are working toward a definitive agreement and are excited to support OpenAI's growth. Yesterday, we celebrated an announcement with Anthropic.

Thanks, Colette. There has been a lot of talk about an AI bubble. From our vantage point, we see something very different. As a reminder, NVIDIA is unlike any other accelerator. We excel at every phase of AI, from Pre-training and Post-training to Inference. With our two-decade investment in CUDA-X acceleration libraries, we are also exceptional at Science and Engineering Simulations, Computer Graphics, Structured Data Processing to Classical Machine Learning.

The world is undergoing three massive platform shifts at once, the 1st time since the Dawn of Moore's Law. NVIDIA is uniquely addressing each of the three transformations. The 1st transition is from CPU General-purpose Computing to GPU Accelerated Computing as Moore's Law slows. The world has a massive investment in non-AI software, from data processing to Science and Engineering Simulations, representing hundreds of billions of dollars in compute cloud computing spend each year. Many of these applications, which ran once exclusively on CPUs, are now rapidly shifting to CUDA GPUs. Accelerated Computing has reached a tipping point. Secondly, AI has also reached a tipping point and is transforming existing applications while enabling entirely new ones. For existing applications, Generative AI is replacing Classical Machine Learning in search ranking, Recommender Systems, ad targeting, click-through prediction to content moderation, the very foundations of Hyperscale Infrastructure.

Meta's Gem, a foundation model for Ad recommendations trained on large-scale GPU clusters, exemplifies this shift. In Q2, Meta reported over a 5% increase in Ad conversions on Instagram and 3% gain on Facebook feed, driven by Generative AI-based Gem. Transitioning to Generative AI represents substantial revenue gains for Hyperscalers. Now, a new wave is rising: Agentic AI systems capable of reasoning, planning, and using tools. From coding assistants like Cursor and Claude Code to radiology tools like iDoc, legal assistants like Harvey, and AI chauffeurs like Tesla FSD and Waymo, these systems mark the next frontier of computing. The fastest-growing companies in the world today—OpenAI, Anthropic, xAI, Google, Cursor, Lovable, Replit, Cognition AI, OpenEvidence, Abridge, Tesla—are pioneering Agentic AI. There are three massive platform shifts. The transition to Accelerated Computing is foundational and necessary, essential in a Post-Moore's Law era.

The transition to Generative AI is transformational and necessary, supercharging existing applications and business models. The transition to Agentic and Physical AI will be revolutionary, giving rise to new applications, companies, products, and services. As you consider infrastructure investments, consider these three fundamental dynamics. Each will contribute to infrastructure growth in the coming years. NVIDIA is chosen because our singular architecture enables all three transitions, and thus so for any form and modality of AI across all industries, across every phase of AI, across all of the diverse computing needs in a cloud, and also from cloud to enterprise to robots. One architecture. Toshiya, back to you.

We will now open the call for questions.